Postdoc: Structural Digital Twin & AI for Infrastructure

New York University; Al Ruways Industrial City; On-site; AED 22,000 - 32,000; Full time

Benefits offered by this job

Medical insurance

Housing allowance

Annual home-leave travel

Educational subsidies

Job summary

NewYork University AbuDhabi invites applications for a Post-Doctoral Associate in Structural Digital Twin. The role involves developing ML-enabled digital twins for civil structures, integrating data from tests, sensors, and simulations, and advancing computational models within a multidisciplinary SHORES-centered program.

The successful candidate will work with faculty, postdocs, and engineers to validate models, publish results, and contribute to project proposals while ensuring research

Qualifications

• PhD in Civil Engineering, Engineering Mechanics, Mechanical Engineering, or closely related field.
• No more than five years of research or professional experience after the PhD.
• Demonstrated research experience in structural modeling and machine learning model development.
• Excellent technical writing, presentation, and interdisciplinary communication skills.

Responsibilities

• Develop computational models that represent the structural response, deterioration, and performance of civil engineering systems.
• Create machine learning and artificial intelligence models for predicting structural behavior under different loading and environmental conditions.
• Integrate numerical models, sensor measurements, laboratory observations, and experimental findings within a digital twin framework.
• Conduct structural and geotechnical simulations using commercial and research‑oriented engineering software.
• Design physical experiments that generate reliable data for model calibration and validation.
• Support laboratory testing involving structural components, soil‑structure systems, or geotechnical applications.
• Configure instrumentation and data‑acquisition systems for structural sensing and health monitoring.
• Process time‑series, sensor, experimental, and simulation data using appropriate computational methods.
• Compare digital twin predictions with physical test results and monitoring measurements.
• Quantify model accuracy, uncertainty, sensitivity, and generalization across different structural conditions.
• Refine computational and machine learning models based on observed discrepancies.
• Develop reproducible data‑processing, model‑training, and validation workflows.
• Maintain organized research code, datasets, technical documentation, and experimental records.
• Collaborate with faculty members, postdoctoral researchers, engineers, students, and multidisciplinary project partners.
• Prepare manuscripts for peer‑reviewed journals and present findings at conferences, seminars, and research meetings.
• Contribute to research proposals, progress reports, technical presentations, and future project development.
• Follow laboratory safety, research ethics, data‑management, and institutional compliance requirements.

Skills

Structural engineering

Structural digital twins

Machine learning

Artificial intelligence

Structural modeling

Geotechnical modeling

Engineering mechanics

Finite element analysis

Computational mechanics

Structural health monitoring

Education

PhD in Civil Engineering

Job description

NewYork University AbuDhabi invites applications for a Post-Doctoral Associate in Structural Digital Twin. The role involves developing ML-enabled digital twins for civil structures, integrating data from tests, sensors, and simulations, and advancing computational models within a multidisciplinary SHORES-centered program.

The successful candidate will work with faculty, postdocs, and engineers to validate models, publish results, and contribute to project proposals while ensuring research